Apache Cassandra is a free and open-source NoSQL database management system that is designed to handle large amounts of data with no single point of failure. In this post, I’m going to highlight 3 different but useful tools that make life easier when using Apache Cassandra.
The first tool that I’m going to talk about is called Zipkin. It is a distributed tracing system that helps gather timing data needed to troubleshoot latency problems in service architectures. Primary features include the collection and lookup of said data. Zipkin uses trace IDs to find and summarize data otherwise you can also query data based on various attributes.
The image above shows the dependencies between the traced requests through each app. Zipkin uses tools such as Kafka to report data. That data is then stored in memory, or persistently with a supported back-end such as Apache Cassandra or Elasticsearch.
The second tool we are going to talk about is called Newts. It is a massively scalable time-series data store based on Apache Cassandra. Time-series data is data that collectively represents how a system/process/behavior changes over time. This type of data-set only tracks changes to the overall system as INSERTs, not UPDATEs. The main features of this tool include:
Finally, the last tool I’m going to talk about is called RESTBase. This is a tool that provides a high-level table storage service abstraction similar to Amazon DynamoDB or Google DataStore on top of Apache Cassandra. It’s main features include:
Cassandra.Link is a knowledge base that our team created to act as a central POI for all things Apache Cassandra. Our goal with Cassandra.Link was to not only fill the gap of Planet Cassandra but we want to bring the Cassandra community, no matter what variant they use, together. Feel free to reach out if you wish to collaborate with us on this project in any capacity.
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